Where change is welcome.
The best way to understand something is through concrete examples. I’ve put together seven examples of data pipelines that represent very typical patterns that we see our customers engage in. These are also patterns that are frequently encountered by data…
Spark is a widely used platform for businesses today because of its support for a broad range of use cases. Developed in 2009 at U.C. Berkeley, Apache Spark has become a leading big data distributed processing framework for its fast,…
One crucial part of Big Data is streaming data. As the name suggests, streaming data refers to data that undergoes continuous generation from multiple sources like social media, CRM, and ERM platforms. Handling and analyzing streaming data can be complex,…
A successful data migration strategy involves moving data from one source to another with as little friction as possible. That friction usually comes in cost, data loss, or downtime accessing the target or destination data sources. A good migration design…
This blog post was updated March 14, 2023 Data pipeline architecture refers to the design of systems and schema that help collect, transform, and make data available for business needs. This data pipeline architecture involves tools and technologies for data…
The benefits of data warehouses are numerous and they have become essential for organizations dealing with massive amounts of data, and while other alternatives come to market their adoption remains on the rise. This increased adoption accounts for a projected…
While some might observe that the difference between slowly changing dimensions (SCD) And Change Data Capture (CDC) might be subtle, there is in fact a technical difference between the two processes. Both processes detect changes in a source database and…
An organization rarely has a single data source. Instead, it aggregates data from various sources like websites, applications, social media, and databases to make data easily accessible through data integration technologies. In addition, this data needs to be transformed before…
Whether you are building your very first pipeline or you’re an old pro, these best practices for building data pipelines can help you make pipelines that are easy to understand and therefore easy to maintain and extend. Design Data Pipelines…
Data lacks value until organizations can gain business intelligence and insights from it. The ability to transform and maximize the value of an organization's data can be challenging for most businesses. Data storage options must hold company data and be…